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A0837
Title: Predicting risks of temperature extremes using large-scale circulation patterns with r-Pareto processes Authors:  Jonathan Koh - University of Bern (Switzerland) [presenting]
Abstract: Many severe weather patterns in the mid-latitudes have been found to be connected to a particular atmospheric pattern known as blocking. This pattern obstructs the prevailing westerly large-scale atmospheric flow, changing flow anomalies in the vicinity of the blocking system to sustain weather conditions in the immediate region of its occurrence. Blocking presence and characteristics are thus important for the development of temperature extremes, which are rarely isolated in space, so one must not just account for their occurrence probabilities and intensities but also their spatial dependencies when assessing their associated risk. A methodology is proposed that does so by combining tools from the spatial extremes and machine learning to incorporate 500hPa geopotential (Z500) anomalies over the North Atlantic and European region as covariates to predict surface temperature extremes. This involves fitting Generalized r-Pareto processes with appropriate risk functionals to daily high-impact positive and negative temperature anomaly events across central Europe from 1979-2020, using loss functions motivated by extreme-value theory in a gradient boosting algorithm. It is checked by simulation that the model parameters are identifiable and can be estimated adequately. It is found which circulation patterns in the Euro-Atlantic sector are most important in determining the characteristics of these extremes and showing how they affect them.